Systems, apparatuses, and methods for fluid analysis and monitoring

ABSTRACT

The present disclosure provides systems, apparatuses, and methods for fluid analysis. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and real-time data may be collected from the fluid via the sampling system. The sampling system may process and transmit the real-time data to the analytical system. The analytical system may include a command and control system that may receive and store the real-time data in a database and compare the real-time data to existing data for the fluid in the database to identify conditions in the fluid.

This application claims the benefit of U.S. Provisional PatentApplication Nos. 62/153,263, filed Apr. 27, 2015, 62/205,315, filed Aug.14, 2015, and 62/237,694, filed Oct. 6, 2015, all of which areincorporated herein by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic of a fluid analysis system, according to anexemplary embodiment of the present disclosure.

FIG. 2 is a schematic of a fluid analysis system, according to anexemplary embodiment of the present disclosure.

FIG. 3 is a schematic of a cooling system, according to an exemplaryembodiment of the present disclosure.

FIG. 4 is a schematic of a cooling system, according to an exemplaryembodiment of the present disclosure.

FIG. 5 is a schematic of a cooling system, according to an exemplaryembodiment of the present disclosure.

FIG. 6 is a schematic of a cooling system, according to an exemplaryembodiment of the present disclosure.

FIG. 7 is a schematic of a sampling system, according to an exemplaryembodiment of the present disclosure.

FIG. 8 is a schematic of a sub-sampling system, according to anexemplary embodiment of the present disclosure.

FIG. 9 is a schematic of a Raman sub-sampling system, according to anexemplary embodiment of the present disclosure.

FIG. 9A is an illustration of inner components of a Raman probe,according to an exemplary embodiment of the present disclosure.

FIG. 10 is a schematic of a fluorescence sub-sampling system, accordingto an exemplary embodiment of the present disclosure.

FIG. 10A is an illustration of a reflection probe, according to anexemplary embodiment of the present disclosure.

FIG. 11 is a schematic of an absorbance sub-sampling system, accordingto an exemplary embodiment of the present disclosure.

FIG. 11A is an illustration of a transmission dip probe, according to anexemplary embodiment of the present disclosure.

FIG. 12 is a schematic of a Fourier Transform IR absorbance sub-samplingsystem, according to an exemplary embodiment of the present disclosure.

FIG. 12A is a schematic of the Fourier Transform Infrared Spectroscopy(FTIR) process in the Fourier Transform IR absorbance sub-samplingsystem shown in FIG. 12.

FIG. 13 is a schematic of an absorbance/fluorescence/scattersub-sampling system, according to an exemplary embodiment of the presentdisclosure.

FIG. 14 is a schematic of a fluid analysis system with a nano chip plug,according to an exemplary embodiment of the present disclosure.

FIG. 15 is an illustration of interior components of a nano chip plugfor use in a fluid analysis system, according to an exemplary embodimentof the present disclosure.

FIG. 16 is a schematic of a fluid analysis system with a nano chip plug,according to an exemplary embodiment of the present disclosure.

FIG. 17 is a flowchart of a fluid analysis system, according to anexemplary embodiment of the present disclosure.

FIG. 18 is a flowchart of an analytical system, according to anexemplary embodiment of the present disclosure.

DESCRIPTION OF EMBODIMENTS

Current fluid analysis systems, including oil and water analysissystems, are inefficient, inaccurate, slow, and/or expensive tomaintain. Particularly, in current oil analysis systems: over 50% of oilanalysis sample readouts may be returned as inconclusive; extraction ofoil samples may lead to contamination of the samples such that theresults may be inaccurate; analysis reporting may take as long as sevento ten days after the sample is drawn and lead to “stale” results,thereby minimizing a user's opportunity for preventative action;sampling methods may require the use, storage, and disposal of plasticbottles as well as the oil samples, which may have a negativeenvironmental impact; samples may typically have to be shipped to a labwhich may increase costs and delays; analysis capabilities on each oilsample may be limited to measuring wear metals and viscosity; thoroughanalysis and reporting may be exponentially more expensive, leading todelays between drawing the sample and receiving the report, along withadditional related costs; and in most current systems, equipment usersdo not have a consistent or effective method for storing and managingthe data gathered from each analysis, so the opportunity to identifytrends or inherent deficiencies in the analysis may be lost.

Oil analysis systems for engine oil may involve additional complexitiesin that the oil being analyzed may include several contaminants producedby the engine when in operation that may lead to engine damage. Thesecontaminants include solids (carbon), liquids (moisture), and gases thatmay lead to thermal breakdown of the engine oil, resulting in lessprotection of engine components and eventual wear and failure of engineparts. Thermal breakdowns occur when the build-up of solid, liquid,and/or gaseous contaminants from the combustion process change themolecular structure of engine oil, leading to an increase in the oil'sviscosity.

Similarly, current water analysis systems either have severallimitations or are virtually non-existent. These limitations are evidentfrom the recent water crisis in Flint, Mich., as well as the recurring(and slow responses to) water boil advisories in cities such as NewOrleans, La. Further, private well owners rarely get their well watertested due to the presence of a septic system nearby, creatingsituations where contaminated water may be consumed. Additionally, stormwater during heavy rains may cause problems for waste water treatmentand contaminate sourced drinking water.

Providing a faster, more accurate and efficient real-time water analysissystem is critical because water is the most important resource forhuman survival, particularly clean water for consumption. Knowing wateris contaminated before being consumed is vitally important forpreventing outbreaks, epidemics, illnesses and deaths. The most commoncontaminants in water include microorganisms, nitrate, and arsenic.These contaminants may cause serious illness, and in some circumstances,death. Infants, children, the elderly, and other people with immunedeficiencies are particularly susceptible to serious health effects fromconsuming drinking water with contaminants.

For example, bacteria, viruses, and protozoa (such as Giardia lambliaand Cryptosporidium) are drinking water contaminants that may rapidlycause widespread and serious illnesses. These microbes primarily comefrom human or animal wastes that wash into lakes and rivers or that maybe carried into shallow groundwater aquifers by rain or irrigationwater. Water systems that treat water from reservoirs or rivers beforedistributing it as drinking water rarely involve microbiologicalcontamination. However, water systems that use groundwater from shallowaquifers are generally required to first chlorinate (disinfect) thewater because the aquifers may be susceptible to contamination. Watersystems test for the presence of total coliform and E. coli, two kindsof bacteria that signal the presence of human or animal wastes. Whenthese bacteria are found in a water sample, the water supplier mustimmediately conduct further testing, look for the source ofcontamination, and in some cases, increase water treatment. If theproblem appears serious, the water supplier must inform all customersabout the problem and instruct them to use bottled water or boil theirtap water before they drink it.

Embodiments of the present disclosure relate generally to systems,apparatuses, and methods for fluid analysis, and in exemplary thoughnon-limiting embodiments, to systems, apparatuses, and methods forreal-time online equipment fluid analysis and monitoring.

Embodiments of the present disclosure may be used to determine thestatus and/or properties of a fluid at any time and at any location asneeded to fit a user's needs. Embodiments provide for a real-time fluidanalysis system including a sampling system and an analytical systemconnected to the sampling system. A fluid may be routed through thesampling system and real-time data may be collected from the fluid. Thesampling system may process and transmit the real-time data to theanalytical system. The analytical system may include a command andcontrol system configured to receive and store the real-time data in adatabase, and compare the real-time data to existing data for the fluidin the database to identify conditions in the fluid.

Embodiments of the present disclosure provide for a real-time onlineequipment fluid analysis and monitoring system with cloud based datalogging, offering a state-of-the-art, cost efficient fluid monitoringsolution that may reduce operating costs at the point of servicedelivery, provide a proactive preventative maintenance program tominimize equipment downtime, extend equipment life, generate higherresale value on used equipment, and significantly reduce the negativeenvironmental impact compared to existing fluid analysis systems.

Referring to FIG. 1, a real-time fluid analysis system (100) is shown.Fluid analysis system (100) may include an enclosure (300) having acooling system (302) attached/coupled to a sampling system (304), and ananalytical system (400) connected to the sampling system (304). Fluidmay be routed out from a fluid source (200) and into cooling system(302) (shown via arrow, A) for cooling the fluid prior to routing thefluid into sampling system (304) (shown via arrow, A) for collectingreal-time data from the fluid. In an exemplary embodiment, real-timedata may include a “fingerprint” of a fluid sample obtained viaspectroscopy. However, other forms of real-time data/information may beobtained from the fluid sample. Sampling system (304) may then processand transmit the real-time data to the analytical system (400) throughfor e.g. an uplink to a WAN (Wide Area Network)/encrypted connection viafor e.g., cellular, satellite, Wi-Fi, Bluetooth, and/or Ethernet (RJ-45)connections. Analytical system (400) may be located in the cloud and/oran external storage device. In an example embodiment, external storagedevice (400 a) may be located onboard a ship or other remote structure.A user may access and/or modify the analytical system (400) via for e.g.a web application (HTTP/HTTPS) in a computing device (desktop computer,portable device, etc.) (400 a) through any type of encrypted connectiondescribed herein. Once processing is complete, fluid may be returnedfrom sampling system (304) to cooling system (302) (shown via arrow, B)and eventually back to fluid source (200) (shown via arrow, B). In otherembodiments, if the fluid does not require cooling, fluid may be routeddirectly from fluid source (200) into sampling system (304) and back.

Analytical system (400) may include a command and control system (406)configured to receive and store the real-time data from the fluid in adatabase (402), and compare the real-time data to existing data for thefluid in the database (402) to identify conditions in the fluid. SeeFIG. 1. Particularly, the command and control system (406) may be ahosted software system that may receive the submitted sample of thefluid and process it through a set of existing neural network models forpredictive analysis of properties and conditions of the fluid. Theneural network models may be configured to target any type of fluid tobe analyzed. The resulting output of the sample analysis may bedependent on the fluid submitted, the networks processed, and thestatistical percentage accuracy of the given neural network model. Invarious embodiments, a user may update the existing neural networkmodels or build new neural network models (via “training”) if thereal-time data does not correspond to any of the set of existing neuralnetwork models. In particular embodiments, command and control system(406) may then deploy the updated and/or new neural network models backto the fluid analysis system (100), including the sampling system (304).In various embodiments, command and control system (406) may also beconfigured to manage a user/client's security and customized settings.

Database (402) may be located in the cloud or in any other type ofexternal storage device. Database (402) may be used to collect and storereal-time data relating to different types of fluids (including types ofoil and water) and their conditions. Fluids may include but are notlimited to any type of industrial fluids or liquids, such as coolants,waste water, etc. Oils may include any type of oil, including but notlimited to very light oils such as jet fuels and gasoline, light oilssuch as diesel, No. 2 fuel oil, and light crudes, medium oils such asmost crude oils, and heavy oils such as heavy crude oils, No. 6 fueloil, and Bunker C. The different “conditions” of oil samples may includebut are not limited to wear metals, additives, viscosity, water, TAN,TBN, and particle counts. In exemplary embodiments, the existingreal-time data in database (402) may include “fingerprint” informationcontaining the molecular content or makeup of different types of fluid.

In some embodiments, base fluid sensor dashboards may also be providedfor each site at time of installation of system (100). Each approveduser may have the ability to customize or alter these dashboards asdesired. In exemplary embodiments, software in the dashboards mayprovide real-time monitoring and graphical updates at an update rate notto exceed 180 seconds or at a data change occurrence. Real-time displayinclusive of graphical depictions may be capable of continuous updateswhile data is being viewed. All data screens and access capabilities maybe automatically resized to fit the viewing area of the device used toaccess the dashboards. Data acquisition and analytics in the dashboardsmay include but is not limited to the following capabilities: analyticalcomparatives and real-time updates (between sampling system (304) andanalytical system (400)); predictive oil changing comparative analysis,chronograph data, financial comparative data; data regarding wearmetals, particulate counts, viscosity, TAN, TBN, Nitration, Sulfation,Foreign Oils, Solvents, Glycol, Soot, Dissolved Gases, and/or OilAdditive Depletion (Zn, Mo, Ph, Ca, Mg, Ba, Na), area plots(illustrating how a customer may view a layout of the system (100)); andnotifications of pending servicing required.

In particular embodiments, enclosure (300) may be a ruggedized andwater-resistant case. For example, enclosure (300) may be mounted viascrews and/or bolts onto a flat surface using for e.g. rubberbushings/shock absorbers to minimize vibrational noise. However,enclosure (300) may include other suitable configurations for securelyholding both cooling system (302) and sampling system (304).

Embodiments of the present disclosure may be designed using a “plug andplay” philosophy. Each component of fluid analysis system (100) may beeasily plugged/snapped to other components of fluid analysis system(100) via connectors (306 a to 306 d) and a wiring harness C. SeeFIG. 1. For example, cooling system (302) may or may not be plugged intosampling system (304) depending on the temperature of the fluid. Inexemplary embodiments, connectors (306 a to 306 d) may be Eaton STC®“snap” connectors allowing for fluid to be routed into and out ofsampling system (304) from cooling system (302).

Referring to FIG. 2, an alternative embodiment of fluid analysis system(100) is shown having substantially the same features as fluid analysissystem (100) shown in FIG. 1. In this embodiment, cooling system (302)may be installed separate from and/or external to enclosure (300) offluid analysis system (100) having sampling system (304). Cooling system(302) may be coupled to enclosure (300)/sampling system (304) viaconnectors (306 a, 306 b) and wiring harness, C. This particularconfiguration provides for greater flexibility by allowing for the fluidanalysis system (100) to be deployed with or without a cooling system(302) as needed to fit a user's needs. In an exemplary embodiment,cooling system (302) may only be coupled to the enclosure (300)/samplingsystem (304) if the fluid being routed through the system (100) requirescooling. In this embodiment, enclosure (300) having sampling system(304) may include a smaller sized case than the embodiment of enclosure(300) having both cooling system (302) and sampling system (304) shownin FIG. 1.

FIG. 3 is a schematic of an exemplary embodiment of cooling system(302). As described herein, cooling system (302) may be a separatelypluggable piece that may be coupled to sampling system (304) if and whena fluid requires cooling, or may come pre-installed within an enclosure(300) along with sampling system (304).

Cooling system (302) may be used to control, filter, and cool fluid (fore.g. oil, water, etc.) to be sampled from a fluid source (200). In anexemplary embodiment, fluid may be oil that is routed from an oil sourcesuch as an engine (200) via pressure from the engine (200) into coolingsystem (302) (shown via arrow, A). Fitting (316 a) may be used toconnect an oil line from a high pressure line from the engine (200) tocooling system (302). In some embodiments, fittings (316 a and 316 b)may be connectors (306) such as an Eaton STC® “snap” connector. In otherembodiments, fittings (316 a and 316 b) may be ½″ FIP fittings. Coolingsystem (302) may include a valve (314 a) connected to source valvemanifold assembly (360) and wiring harness, C. Valve (314 a) may be usedto control when the oil may be allowed into the cooling system (302). Insome embodiments, valve (314 a) may be an electromechanical singledirection solenoid valve. In an exemplary embodiment, valve (314 a) maybe the AS Series Valve offered by Gems™ Sensors & Controls. Sourcemanifold assembly (360) may be the Manifold Assemblies offered by Gems™Sensors & Controls. Valve (314 a) may be controlled via connections to acontroller located in the cooling system (302) and/or located insampling system (304), which controller may send a signal to the valve(314 a) to open and close as needed to allow oil into the cooling system(302).

In various embodiments, oil may first be routed through a filterconnection (318) and into a filter (320) located outside cooling system(302). See FIG. 3. In other embodiments, filter (320) may be locatedinside cooling system (302). Filter connection (318) and filter (320)may be used to prevent for e.g. debris in oil from entering coolingsystem (302) and damaging cooling system (302) and eventually samplingsystem (304). Oil may then be routed into a pressure reducer (regulator)valve with a pressure sensor (308). Pressure reducer valve (308) mayinclude two inputs and one output. See FIG. 3. In an exemplaryembodiment, pressure reducer valve (308) may be the BB-3 seriesstainless steel back-pressure regulator offered by Tescom™. In variousembodiments, pressure reducer valve (308) may reduce the pressure fromdangerously high pressures (>50 psi) in an engine (200) to betweenapproximately 1 and 50 psi (depending on fluid type). Once the oil isreduced to a safe pressure level, oil may be routed into acooler/radiator (324) and then to a temperature sensor (310) and a 2-waysolenoid valve (312). In some embodiments, cooler (324) may either be asimple radiant heat sink or a fluid cooler system. In an exemplaryembodiment, cooler (324) may be the MMOC-10 Universal 10-Row Oil Cooleroffered by Mishimoto™.

In an exemplary embodiment, if the temperature sensor (310) detects thatthe oil is at a temperature </=40° C., it may switch valve (312) androute the oil out of cooling system (302) and into sampling system (304)(shown via arrow, A). See FIG. 3. However, if the temperature sensor(310) detects that the oil is at a temperature >40° C., it may route theoil back into pressure reducer valve (308) and into cooler (324) viavalve (312) until the oil reaches the desired temperature (for e.g. 40°C.). This temperature is relevant because it is related to measuring theoil's viscosity. A lubricating oil's viscosity may be measured eitherbased on its kinematic viscosity or its absolute (dynamic) viscosity. Anoil's kinematic viscosity is defined as its resistance to flow and sheardue to gravity at a given temperature. However, simply stating an oil'sviscosity is meaningless unless the temperature at which the viscositywas measured is defined. For most industrial oils, it is common tomeasure kinematic viscosity at 40° C. because this is the basis for theISO viscosity grading system (ISO 3448). In various embodiments, fan(370) may be installed within cooling system (302) and turned on asneeded (for e.g. if the temperature of the oil is >40° C.) to assistcooler (324) in cooling the oil based on the temperature of the fluidand radiant air temperature. See FIG. 3. Fan (370) may be controlled viathe controller described herein in sampling system (304) (e.g., seecontroller (332) shown in FIG. 7) and/or cooling system (302) (notshown).

Wiring harness, C, may be used to connect various connections of coolingsystem (302) described herein to sampling system (304). See FIG. 3. Oncethe oil is adequately sampled by sampling system (304), oil may berouted back from sampling system (304) to cooling system (302) (shownvia arrow, B in FIGS. 1 and 2). To facilitate this return, coolingsystem (302) may include an air valve (322) that may be opened as neededto allow air to purge the line and speed up the return of oil if thereis no pressure to push/drain the oil back into cooling system (302) fromsampling system (304). Oil may then be routed out of cooling system(302) and back to engine (200) via a similar fitting (316 b)-valve (314b)-return valve manifold assembly (362) connection as described hereinfor entry of oil into cooling system (302). See FIG. 3. Return manifoldassembly (362) may be the Manifold Assemblies offered by Gems™ Sensors &Controls.

Referring to FIG. 4, an alternative embodiment of cooling system (302)is shown having substantially the same features as cooling system (302)shown in FIG. 3. In this embodiment, cooling system (302) is shown ashaving connections to multiple fluid sources (200) for cooling androuting fluid into sampling system (304). In a particular embodiment,fluid from only one fluid source may be cooled and sampled at a time. Inan exemplary embodiment, cooling system (302) may be simultaneouslyconnected to two engines (200), with multiple fittings (316 a to 316 d)and valves (314 a to 314 d) attached to each of the input/inlet andreturn/outlet sides, each of which may be controlled independently basedon the oil to be sampled. As shown, valves (314 a to 314 d) connected toeach of the two engines (200) may be connected to one source manifoldassembly (360) and one return manifold assembly (362). Each valve (314 ato 314 d) may be controlled via connections to a controller located inthe cooling system (302) (not shown) and/or located in sampling system(304) (e.g., controller (332) shown in FIG. 7), which controller maysend a signal to an appropriate valve (314 a to 314 d) on the sourceand/or return manifold assemblies (360, 362) to open to allow flow ofoil, while closing other valves (314 a to 314 d) depending on the sampleand/or engine (200) selected for sampling.

FIG. 5 is a schematic of an alternative embodiment of cooling system(302) having substantially the same features as cooling systems (302)shown in FIGS. 3 and 4. In this embodiment, cooling system (302) mayinclude a pump (326) connected to a fluid source (200) with fluidshaving low/no pressure. Pump (326) may provide additionalpressure/movement for these fluids to be routed into cooling system(302) and eventually into sampling system (304) (e.g., see FIGS. 1 and2). In an exemplary embodiment, oil may be routed from engine (200) intopump (326), which pump (326) may then pump oil into cooling system (302)(shown via arrow, A). Oil may first be routed into filter connection(318)/oil filter (320), pressure reducer valve (308), cooler (324),temperature sensor (310), 2-way solenoid valve (312), sampling system(304) (e.g., see FIGS. 1 and 2), and back to cooling system (302) andengine (200) as described herein. Pump (326) may include connections viawiring harness, C, to sampling system (304). Pump (326) may beinitialized via connections to a controller located in the coolingsystem (302) (not shown) and/or located in sampling system (304) (e.g.,see controller (332) shown in FIG. 7) when a fluid sample is requested.In various embodiments, controller in cooling system (302) and/orsampling system (304) (e.g., see controller (332) shown in FIG. 7) mayshut pump (326) down once sampling is complete, then open air valve(322) as needed to allow air to purge the line and speed up the returnof oil if there is no pressure to push/drain the oil back into coolingsystem (302).

FIG. 6 is a schematic of an alternative embodiment of cooling system(302) having substantially the same features as cooling systems (302)shown in FIGS. 3, 4, and 5. In this embodiment, cooling system (302) mayinclude a pump (326) connected to multiple fluid sources (200) withfluids having low/no pressure. As shown, source valve manifold (360) maybe located external to cooling system (302), thereby preventingduplicative valve (314 a to 314 d) systems on the input line to coolingsystem (302). Further, providing the source valve manifold (360)external to cooling system (302) allows for oil from multiple engines(200) to be sourced into a single line prior to being routed into pump(326), thus eliminating the need for multiple pumps (326). See FIG. 6.As shown, oil may be routed from the two engines (200) into fittings(316 a and 316 b) and valves (314 a and 314 b) attached to a sourcevalve manifold (360). Each valve (314 a to 314 d) may be controlled viaconnections to a controller located in the cooling system (302) (notshown) and/or located in sampling system (304) (e.g., see controller(332) see FIG. 7), which controller may send a signal to an appropriatevalve (314 a to 314 d) on the source and/or return manifold assemblies(360, 362) to open to allow flow of oil, while closing the other valve(314 a and/or 314 b) depending on the sample and/or engine (200)selected for sampling. Once a valve (314 a to 314 d) is opened, oil maybe routed into pump (326), and subsequently pumped into cooling system(302), including the filter connection (318)/oil filter (320), pressurereducer valve (308), cooler (324), temperature sensor (310), 2-waysolenoid valve (312), sampling system (304), and back to cooling system(302) and engine (200) as described herein.

Referring to FIG. 7, a sampling system (304) is shown. As shown, arrow Arepresents fluid being routed in from cooling system (302) and/or fluidsource (200), arrow B represents fluid being returned back to coolingsystem (302) and/or fluid source (200) after sampling, and arrow Crepresents wiring harness connectors between components of samplingsystem (304) and between sampling system (304) and cooling system (302).

Sampling system (304) may include at least one removable and replaceablesub-sampling system (330). Particularly, sampling system (304) mayinclude an “assembly line” of multiple daisy-chained sub-samplingsystems (330) via for e.g. a wiring harness, C. In various embodiments,multiple sub-sampling systems (330) may be stacked on top of each otherand “snap” connected together via for e.g. connectors (306) (e.g., seeFIGS. 1 to 6). See FIG. 7. In particular embodiments, connectors (306)may be the Eaton STC® “snap” connectors allowing for fluid to be routedinto and out of sub-sampling systems (330). In this embodiment, eachsub-sampling system (330) may have a female input connector (on the top)and a male output connector (on the bottom), allowing each sub-samplingsystem (330) to be stacked sequentially to satisfy fluid and targetrequirements. The types of sub-sampling system (330) used for samplingsystem (304) may be dependent on the fluid and targeted identificationcriteria needed.

In various embodiments, sampling system (304) may further includeconnections between input and output fittings (316 a and 316 b), inputand output pressure reducer valves with pressure sensors/transducers(308 a and 308 b), input temperature sensors (310), at least oneviscometer (328), a 2-way solenoid valve (312), and at least onecontroller (332). Particularly, sampling system (304) may includeseveral wiring harness connectors, C, that connect from the at least onecontroller (332) to each sub-sampling system (330) (via for e.g.dovetails for coupling), the at least one viscometer (328), the pressurereducer valves with pressure sensors/transducers (308 a and 308 b),temperature sensors (310), 2-way solenoid valve (312), and a ribbon tothe external connector for the cooling system (302) (e.g., see FIGS. 1to 6). Controller (332) may control the sampling system (304) and/orcooling system (302) and interact with analytical system (400) by fore.g. submitting real-time data obtained from fluids being sampled toanalytical system (400).

Once fluid is routed into sampling system (304), bypass valve (312) maydivert the fluid back to cooling system (302) via a return line if thepressure and/or temperature of the fluid are too high or low. Pressuresensor/transducer (308 a and 308 b) may be located at the output/returnline to perform a pressure comparison between the input and outputpressures of the fluid to determine if a significant enough drop existsto identify the presence of a leak. This may be accomplished duringsampling of the fluids by letting the sub-sampling systems (330)equalize in pressure while the samples are being taken. A change inpressure after equalization, i.e. a drop, may infer the presence of aleak within the sub-sampling systems (330) or at the output valve (308 aand 308 b). To determine if the output valve (308 a and 308 b) isleaking, a user may monitor the current required to operate thesolenoid. As valves driven by solenoids begin to fail, they will drawmore current to perform the same functions (i.e. sticky valve, a short,etc.). Current monitoring on the solenoid valve lines may constituteanother part of self-diagnostics for sampling system (304)/fluidanalysis system (100).

As shown, bypass valve (312) may divert the fluid to the at least oneviscometer (328) if the pressure and/or temperature of the fluid are atan appropriate level. At least one viscometer (328) may be used tomeasure the viscosity and flow parameters of the fluid. In an exemplaryembodiment, viscometer may be the VISCOpro 2000 Process Viscometeroffered by the Petroleum Analyzer Company, L.P. d/b/a PAC. Once theviscosity of the fluid is measured, fluid may be routed into the atleast one sub-sampling system (330). In an exemplary embodiment, fluidmay be routed from the at least one viscometer (328) into threesub-sampling systems (330) stacked on top of other, the fluid beingsampled while in each sub-sampling system (330). See FIG. 7.

All components of sampling system (304) may be connected to controller(332) via wiring harness connectors, C. See FIG. 7. In an exemplaryembodiment, controller (332) may be an ARM (Acorn RISC Machine/AdvancedRISC Machine) based system with a custom shield for connecting tocooling system (302), sub-sampling systems (330), and/or othercomponents of cooling and sampling systems (302, 304) (e.g., see FIGS. 1to 7). In exemplary embodiments, controller (332) may include an RJ45(CATS/6) Ethernet connection (334), an SMA (SubMiniature version A)connection (336) for an antenna or an antenna dongle, and a powerconnector (338). Controller (332) may also include connections includingfor e.g. USB, HDMI, and Bluetooth connections, and may be powered via aMini-USB connection. In exemplary embodiments, controller may be theRaspberry Pi 3 Model B, Raspberry Pi Zero, or Raspberry Pi 1 Model A+.In other embodiments, controller (332) may be the Mojo Board V3 offeredby Embedded Micro—an FPGA (Field Programmable Gate Array) with multiplepre-made shields. Shields used to connect controller (332) to othercomponents of sampling system (304) and/or cooling system (302) (e.g.,see FIGS. 1 to 6) may include the Servo Shield (used for connecting toservos/solenoids on valves), Proto Shield (used for prototyping), IOShield (used for displaying output, buttons for input, and switches forconfiguration options), and/or stackable headers (used to stack shields)offered by Embedded Micro. In some embodiments, controller (332) may beplaced within its own enclosure separate from enclosure (300) ofsampling system (304) to protect controller (332) in case of acatastrophic fluid failure/leak within sampling system (304). In otherembodiments, controller (332) may also be included in cooling system(302).

In exemplary embodiments, controller (332) may include its owncustomized software to assist sampling system (304) in performinganalysis of fluid and sending/receiving real-time data regarding thefluid to analytical system (400). In various embodiments, software ofcontroller (332) may include information including but not limited tocommunication protocols, security settings, sampling system (304)interaction, cooling system (302) sub-controller/controller, temperatureand pressure sensors in system (100), as well as information pertainingto the determination in a spectroscopy based sub-sampling system (330)regarding how to trigger an excitation system and read outputs from thesource from a detection system connected to the source. An exemplaryembodiment of this software will be described in further detail in thediscussion relating to the flowchart of sampling system (304) shown inFIG. 17. In some embodiments, this software of sampling system (304) mayalso monitor the system (100) for leaks and other potential problems.

In a particular embodiment, an onboard sampling system (304) may pollthe analytical system (400) in the cloud every pre-determined number ofminutes for specific commands/instructions. When a sampling system (304)is deployed, its inbuilt software may be pre-keyed with a customlogin/password and/or entered by a user onboard. Upon startup, thatlogin/password may retrieve the configuration settings for that samplingsystem (304), which settings may contain settings entered into thesampling system (304) and any other information that the onboard system(100) can detect from its own hardware. An example setting may be thesampling schedule and retention period of the fluid to be sampled. Witha limited amount of onboard space available for storing sample data, ifthe onboard system (100)/sampling system (304) is expected to be in aremote area/out of contact for an extended period of time and begins tofill its storage with automated samples, it may then have to startdropping samples. Upon establishing a connection to the analyticalsystem (400) in the cloud, the onboard system (100)/sampling system(304) may then proceed to upload all the automated sample data itpreviously stored when disconnected from the internet.

Referring to FIG. 8, a sub-sampling system (330) is shown. Sub-samplingsystem (330) may be a removable and replaceable component/system thatmay be plugged in to sampling system (304) (e.g., see FIG. 7) asnecessary to perform specific types of analysis on a sample of fluidbeing routed through sampling system (304) and obtainreal-time/“fingerprint” information regarding the fluid sample.Combining multiple sub-sampling systems (330) by simply “plugging”multiple sub-sampling systems (330) together during assembly of thesampling system (304) may allow for many different types of fluidsamples to be analyzed, and many different characteristics of thosesamples to be obtained.

In exemplary embodiments, accurate analysis may be performed and precisedata obtained from fluid samples by performing electro-optical analysison the fluids. Sub-sampling system (330) may utilize a spectralscanner/spectrometer/custom electro-optical system to instantaneouslyand continuously scan and inform a user of the molecular makeup andcondition of any fluids such as for e.g. industrial oil and water.Different types of fluids/materials have their own “fingerprint” and theelectro-optical system may read and analyze the differences betweenthese materials. In exemplary embodiments, sub-sampling system (330) maybe at least one of a Raman sub-sampling system (330, 350) (e.g., seeFIG. 9), a fluorescence sub-sampling system (330, 352) (e.g., see FIG.10), an absorbance sub-sampling system (330, 354) (e.g., see FIG. 11), aFourier Transform IR absorbance sub-sampling system (330, 356) (e.g.,see FIG. 12), and an absorbance-fluorescence-scatter sub-sampling system(330, 358) (e.g., see FIG. 13). Each type of electro-optical analysisbased sub-sampling system (330) may provide for different methods ofanalyzing the fluids by identifying different parts of the fluids.

In exemplary embodiments, sub-sampling system (330) (e.g., see FIG. 8)may include connections between pluggable fluid input and outputconnectors (306 a and 306 b) (i.e., a female input on top and a maleoutput on the bottom), a continuous-flow or flow-through electro-opticalsampling chamber (340) connected to a fiber optic probe (342), and fiberoptic cables (348 a, 348 b) connected to both the probe (342) and eachof an excitation source/electromagnetic radiation source (344) and adetection system (346). See FIG. 8. In a particular embodiment, samplingchamber (340) may be a glass, quartz, borosilicate, or polysterenechamber. Sub-sampling system (330) may also include wiring harnessconnections to controller (332) (e.g., see FIG. 7) described herein(shown as arrow C) and a power wire harness connection/power plug topower components of sub-sampling system (330) (shown as arrow D). Wiringharness connector, C, may connect to the microcontroller (332) and insome embodiments, use a dovetail to inter-connect to various componentsof fluid analysis system (100) described herein. In an exemplaryembodiment, power plug/connection, D, may be connected to a powerdistribution unit (PDU) inside the enclosure (300)/sampling system(304).

As shown, fluid may be routed in to sub-sampling system (330) from valve(312) and/or at least one viscometer (328) into sampling chamber (340)for analyzing (e.g., see FIG. 7). Particularly, controller (332) mayflush a sample of the fluid through the chamber (340) for a certain timedepending on the distance between sampling system (304) and fluid source(200) in order to remove previous fluid from other sources (200) and toensure a clean sample. Controller (332) may then close relevant inputand output valves (308 a and 308 b) in sampling system (304) (e.g., seeFIG. 7) and/or valves (314 a to 314 d) in cooling system (302) (e.g.,see FIGS. 3 to 6) to stop fluid flow. Controller (332) may then be usedin conjunction with probe (342), excitation source (344), and detectionsystem (346) to obtain real-time data/fingerprint information regardingthe fluid (e.g., see FIG. 8). Particularly, controller (332) may begincollecting samples by triggering the excitation source (344) andsimultaneously reading the resulting fluid real-time data from thedetection system (346). The still nature of the fluid sample in thesampling chamber (340) may further allow for application of timeresolved optical spectroscopy to the fluid. Once adequate sampling hasbeen performed (and relevant real-time data obtained) on fluid samples,fluid may be routed to another sub-sampling system (330) and/or returnedback to cooling system (shown via arrow B).

In exemplary embodiments, controller (332) may also, based on learnedfeedback from the sampling system (304), adjust the focus of the probe(342) by increasing or decreasing the distance of the probe to thesampling chamber (340). While adjusting this distance, controller (332)may continually take samples to try to match a known good focus. Theknown good focus may be established via samples from the specific fluidin question that may already be stored in database (402) prior toinstallation of system (100). A focus calibration may be issued manuallyor automatically during a focus run, or based on a baselinestandardization sample. In various embodiments, the focal distance ofprobe (342) may be adjustable during setup (via commands frommicrocontroller (332)) so as to obtain the highest resolution samples ofthe fluid. Particularly, controller (322) may utilize a worm gear ortype of dynamic adjuster/glide system controller to adjust the focus ofthe probe (342).

Excitation source (344) and detection system (346) may be used in tandemto perform fluid analysis (e.g., see FIG. 8). Detection system (346) mayact as electro-optical “eyes” for a given excitation source (344).Controller (332) may inform the detection system (346) to prepare forsampling, after which it may inform the excitation source (344) to“fire” electromagnetic radiation into the fluid sample, and thedetection system (346) may then register the results of this “firing”.In exemplary embodiments, this “firing” may be milliseconds to secondslong depending on the excitation source used and the type of detectionrequired. In particular embodiments, excitation source (344) may be anLED source (specific chromatic source, mono chromatic, UV), IR/NIR(infrared/near-infrared) source, and/or wavelength stabilized laser(specific wavelength laser for excitation). In various embodiments,detection system (346) may be a type of charge-coupled device (CCD)(that may simply report direct data without a spectrometer forfiltering), a set of photodiodes with a matching set of spectral filters(looking for specific wavelengths), and/or a spectrometer coupled to athermally controlled CCD that may detect multiple sources coupled to thespectrometer for filtering.

In some embodiments, sub-sampling systems (330) may be furtherconfigured to divert approximately 1 to 10 mL of the fluid samples beinganalyzed into a retrieval storage compartment/container within samplingsystem (304). Doing so may allow for the fluid sample to be analyzed viaGas Chromatography/Mass Spectrometry if the analytical system (400)determines that it cannot accurately identify the sample it has beengiven. In various embodiments, sub-sampling system (330) may include aport wherein the compartment/container containing the fluid sample maybe removed and/or shipped to an external location for further processingand analyzing.

Referring to FIG. 9, a Raman sub-sampling system (330, 350) is shown.FIG. 9A is an illustration of inner components of a Raman probe (342).Raman sub-sampling system (330, 350) substantially includes similarfeatures as the sub-sampling system (330) described herein in FIG. 8,with particular modifications made to the type of probe (342 a),excitation source (344), and detection system (346).

Raman spectroscopy is a spectroscopic technique for obtaininginformation about molecular vibrations of a sample that may be used forsample identification and quantitation. The technique involves shining alight source (e.g., laser) on a sample and detecting the scatteredlight. The majority of the scattered light may be of the same frequencyas the excitation source, known as Rayleigh or elastic scattering. Avery small amount of the scattered light may be shifted in energy fromthe laser frequency due to interactions between the incidentelectromagnetic waves and the vibrational energy levels of the moleculesin the sample. Plotting the intensity of this “shifted” light versusfrequency results in a Raman spectrum of the sample (“Raman shift”).Generally, Raman spectra are plotted with respect to the laser frequencysuch that the Rayleigh band lies at 0 cm⁻¹. On this scale, the bandpositions will lie at frequencies that correspond to the energy levelsof different functional group vibrations.

In exemplary embodiments, a “fingerprint” of a fluid sample may beobtained from a Raman sub-sampling system (330, 350) via a singlefrequency wavelength that uses a specialized Raman probe (342 a) tocapture the “scatter” of molecular energy level changes. In exemplaryembodiments, Raman sub-sampling system (330, 350) may include aspecialized Raman probe (342 a), a stabilized wavelength laser (344),and a set of photo diodes and spectral filters (346) targeting therequired wavelengths of a Raman shift. In various embodiments, chamber(340) may be quartz or glass flow-through/continuous flow chamber basedon the wavelength and power of the laser (344). For example, if thelaser (344) is in the UV range, then chamber (340) may be a quartzchamber. In exemplary embodiments, laser (344) may be a 785 nmwavelength optical pumped Raman laser. In particular embodiments, Ramanprobe (342 a) may be the General Purpose Raman Probes offered by OceanOptics, Inc.

As shown in FIG. 9A, the excitation EM (electro-magnetic) source may beemitted into excitation fiber and through a band-pass wavelength filterand a dichroic filter of the Raman probe (342 a). The reflected EMsource may then scatter against the dichroic filter, reflect off amirror and through a long-pass wavelength filter and collection fiber,and be transported via fiber optic cable (348 a) (e.g., see FIG. 9) andcollected on the photodiodes (346). Raman probe (342 a) may be used tomeasure the wavelength shift(s) (Raman shift) of the excited sample.These Raman shifts may show up as peaks in a spectral graph. The Ramanshifts may be converted to wavelengths via the following formulas:

${Wavenumbers} - {{Wavelength}\mspace{31mu}\hat{v}} - \frac{10000}{\lambda}$${Wavenumbers} - {{Frequency}\mspace{31mu}\hat{v}} - \frac{v}{100 \cdot c}$${Wavenumbers} - {{Electron}\mspace{14mu}{volt}\mspace{31mu}\hat{v}} - {\frac{e}{h \cdot c} \cdot \frac{E}{100}}$

-   -   {circumflex over (v)}: Wavenumbers (cm⁻¹)    -   λ: Wavelength (μm)    -   ν: Frequency (s⁻¹)    -   c: Velocity of light (2.99792458·10⁸ m/s)    -   e: Elementary charge (1.60217733·10⁻¹⁹ C)    -   h: Planck's constant (6.6260755·10⁻³⁴ J·s)    -   E: Energy (eV)

In exemplary embodiments, the “fingerprint” of the fluid sample may beobtained by measuring/determining the value of this “Raman shift”.

Referring to FIG. 10, a fluorescence sub-sampling system (330, 352) isshown. FIG. 10A is an illustration of a type of reflection probe (342 b)used in fluorescence sub-sampling system (330, 352). Fluorescencesub-sampling system (330, 352) substantially includes similar featuresas the sub-sampling system (330) described herein in FIG. 8, withparticular modifications made to the type of probe (342 b), excitationsource (344), and detection system (346).

Fluorescence spectroscopy based systems utilize electromagneticspectroscopy to analyze fluorescence from a sample. These systems mayinvolve using a beam of light, usually ultraviolet light, that excitesthe electrons in molecules of certain compounds and causes them to emitlight; typically, but not necessarily, visible light. Fluorescencesub-sampling/detection systems may generally require at least: anexcitation light source, a fluorophore (fluorescent chemical compoundthat can re-emit light upon light excitation), wavelength filters toisolate emission photons from excitation photons, and a detector thatregisters emission photons and produces a recordable output, usually asan electrical signal.

A “fingerprint” of a fluid sample may be obtained from a fluorescencesub-sampling system (330, 352) based on the following technology: Usinga light source that will shine broadband light (i.e., light in manywavelengths) allows for the ability to emit photons in various energies.When the light source shines on a fluid/oil sample, photons in the lightpenetrate into the sample, meeting in their way the molecules thatcompose the sample. Each of the molecules in the sample has its ownspecific set of energy, and if a photon with a certain energy hits amolecule, the photon may simply disappear. Out of the billions ofphotons sent by the light source, some of them maydisappear—particularly, those with energy that matches the sample'svibrations. After the photons penetrate into the sample and repeatedlyhit the sample's molecules, some of the photons may leave the sample. Atthis point, it is important to “ask” these photons what they have seen,which may be done by analyzing the color of the light that comes out ofthe sample. Some wavelengths in the light may be missing, or moreprecisely, some wavelengths in the light may be attenuated relative tothe others. These wavelengths are the ones that match the sample'senergy vibrations, and therefore constitute thetransmission/absorbance/fluorescence “fingerprints” of the sample. Thus,in an exemplary embodiment of the present disclosure, to obtain a“fingerprint” of a sample via fluorescence spectroscopy, a broadbandlight source may first be shined on a sample. Light coming out of thesample may then be collected and the wavelength content of the light maybe analyzed. The molecular content of the sample may then be analyzedand determined by comparing the wavelength of the light that wasinitially sent/shined on the sample with the wavelength of the lightthat was collected after leaving the sample.

In exemplary embodiments, fluorescence sub-sampling system (330, 352)may include a reflection probe (342 b), an LED source (344) connected tothe probe (342 b), and a detector (346) connected to the probe (342 b)used to measure parameters of fluorescence of the sample, including itsintensity and wavelength distribution of emission spectrum afterexcitation by a certain spectrum of light, which parameters may be usedto identify the presence and the amount of specific molecules in thesample. In various embodiments, chamber (340) may be quartz orpolystyrene flowthrough cell/continuous flow chamber. For example, ifsource (344) is a low power LED source, then chamber (340) may be apolystyrene chamber. In exemplary embodiments, source (344) may be a240-627 nm LED source connected to reflection probe (342 b).Alternatively, a UV source (344) may be utilized if a wider source rangeis needed. In a particular embodiment, reflection probe (342 b) may bethe premium-grade reflection probes manufactured by Ocean Optics, Inc.See FIG. 10A. In various embodiments, the detector (346) may be afluorometer that may require a spectral filter equal to the excitationsource to filter out that light, but also detect all other wavelengthsfrom source (344). In embodiments, detector (346) may utilize a set ofphotodiodes with spectral filters or a CCD. In either embodiment, thelight emitted from the energy state transition, quenching, or absorptionmay be converted to an electrical signal by the detection system (346)and then transmitted back to the controller (332) (e.g., see FIG. 7) foridentification of “fingerprint” information of the fluid sample.

FIG. 11 is a schematic of an absorbance sub-sampling system (330, 354).FIG. 11A is an illustration of a type of transmission dip probe used inabsorbance sub-sampling system (330, 354). Absorbance sub-samplingsystem (330, 354) substantially includes similar features as thesub-sampling system (330) described herein in FIG. 8, with particularmodifications made to the type of probe (342 c), excitation source(344), and detection system (346).

Absorbance spectroscopy, commonly referred to as spectrophotometry, isthe analytical technique based on measuring the amount of light absorbedby a sample at a given wavelength. Molecular absorption spectroscopy inthe ultraviolet (UV) and visible (VIS) portions of the electromagneticspectrum relates to the measured absorption of radiation in its passagethrough a gas, a liquid, or a solid. Generally, the wavelength regionused may be from approximately 190 to 1000 nm, and the absorbing mediummay be at room temperature.

In embodiments of the present disclosure, obtaining a “fingerprint” of asample via absorbance spectroscopy may include the same general methodsas described herein for obtaining a fingerprint of a sample viafluorescence spectroscopy. In exemplary embodiments, a broadband lightsource may first be shined on a sample. Light coming out of the samplemay then be collected and the wavelength content of the light may beanalyzed. The molecular content of the sample may then be analyzed anddetermined by comparing the wavelength of the light that was initiallysent/shined on the sample with the wavelength of the light that wascollected after leaving the sample.

In exemplary embodiments, absorbance sub-sampling system (330, 354) mayinclude a transmission dip probe (342 c), a near infrared (NIR) source(344) connected to probe (342 c), and a detector (346) connected toprobe (342 c) that measures the output (transmission) from the source(344) after passing through the sample, where the difference between theinput and output is the absorption amount, i.e., the “fingerprint” ofthe sample. In various embodiments, chamber (340) may be a quartzflow-through cell/continuous flow chamber. In exemplary embodiments,source (344) may be a 1000-5000 nm NIR source connected to transmissiondip probe (342 c). Alternatively, a UV source (344) may be utilized if awider source range is needed. In some embodiments, source (344) mayinclude infrared and/or visible sources (usually 190 to 1000 nm). In aparticular embodiment, transmission dip probe (342 c) may be theTP300-Series Transmission Probes offered by Ocean Optics, Inc. See FIG.11A. In various embodiments, the detector (346) used for detection mayutilize a CCD or a set of photodiodes with spectral filters formeasuring the intensity of resultant wavelengths compared to source.

FIG. 12 is a schematic of a Fourier Transform IR absorbance sub-samplingsystem (330, 356). FIG. 12A is a schematic of the Fourier transforminfrared spectroscopy (FTIR) process in the Fourier Transform IRabsorbance sub-sampling system (330, 356). Fourier Transform IRabsorbance sub-sampling system (330, 356) substantially includes similarfeatures as the sub-sampling system (330) described herein in FIG. 8,with particular modifications made to the type of probe (342 d),excitation source (344), and detection system (346).

Fourier transform infrared spectroscopy (FTIR) is a form of absorbancespectroscopy used to obtain an infrared spectrum of absorption oremission of a solid, liquid or gas. An FTIR spectrometer maysimultaneously collect high spectral resolution data over a widespectral range. In exemplary embodiments of the present disclosure,obtaining a “fingerprint” of a sample via FTIR may include the samegeneral methods as described herein for obtaining a fingerprint of asample via absorbance spectroscopy. For example, infrared (IR) radiationmay be first passed through the sample. Some of the IR radiation may beabsorbed by the sample and some of it may pass through (transmitted).The resulting spectrum represents the molecular absorption andtransmission, thereby creating a molecular “fingerprint” of the sample.The “fingerprint” includes absorption peaks which correspond to thefrequencies of vibrations between the bonds of the atoms making up thesample. Because each different material constitutes a unique combinationof atoms, no two compounds produce the exact same IR spectrum, therebyallowing for positive identification of different kinds of material viaqualitative analysis. In fact, the size of the absorption peaks in thespectrum indicates the exact amount of material present.

In exemplary embodiments, Fourier Transform IR absorbance sub-samplingsystem (330, 356) may include substantially the same features asabsorbance sub-sampling system (330, 354), including a transmission dipprobe (342 d), a near infrared (NIR) source (344), and detector (346).However, Fourier Transform IR absorbance sub-sampling system (330, 356)may include an additional interferometer (344 d) between source (344)and probe (348 d) to measure an entire range of a wavelength of a sampleat once. See FIG. 12. In various embodiments, chamber (340) may be aquartz flow-through cell/continuous flow chamber. In exemplaryembodiments, source (344) may be a 1000-5000 nm NIR source connected totransmission dip probe (342 d). Source (344) may be a monochromaticsource. Alternatively, other sources (344) in the NIR to infraredspectrum may be used. In some embodiments, source (344) may includeinfrared and/or visible sources (usually 190 to 1000 nm). In aparticular embodiment, transmission dip probe (342 d) may be theTP300-Series Transmission Probes offered by Ocean Optics, Inc. See FIG.11A.

In an exemplary embodiment, as shown in FIG. 12A, infrared energy/beammay be emitted from the source (344) towards the interferometer. Thisbeam may then enter the interferometer where “spectral encoding” maytake place. The resulting interferogram signal may then exit theinterferometer and towards the chamber (340), where it may betransmitted through or reflected off of the surface of the fluid samplein chamber (340), depending on the type of analysis being accomplished.This is where specific frequencies of energy, which are uniquelycharacteristic of the sample, are absorbed. Although not shown, probe(342 d) may then pick up the resulting output from the sample and passthis output to the detector (346) for final measurement. Detector (346)used may be specially designed to measure the special interferogramsignal. The measured signal may then be digitized and sent to controller(332) in sampling system (304) (e.g., see FIG. 7), which may send thesignal to analytical system (400) (e.g., see FIGS. 1 and 2) where theFourier transformation may take place. Comparing the final IR spectrumto a background spectrum (measurement with no sample in the beam) mayallow for identification of spectral features solely present in thesample. In exemplary embodiments, analytical system (400) may decode thesignal received from controller (332) using Fourier Transform Infra-redcalculations to obtain the “fingerprint” of a fluid sample.

Referring to FIG. 13, a schematic of an absorbance/fluorescence/scattersub-sampling system (330, 358) is shown. Absorbance/fluorescence/scattersub-sampling system (330, 358) substantially includes similar featuresas the sub-sampling systems (330) described herein in FIG. 8, withparticular modifications made to the type of probe (342 e), excitationsource (344), and detection system (346), as well as additional fiberoptic cables (348 b, 348 c, 348 d) between probe (342 e) and detectionsystem (346).

Particularly, absorbance/fluorescence/scatter sub-sampling system (330,358) may combine features of both the fluorescence and absorbancesub-sampling systems (330, 352), (330, 354), described herein withreference to FIGS. 10 and 11, respectively. In exemplary embodiments,absorbance/fluorescence/scatter sub-sampling system (330, 358) mayinclude a reflection and/or transmission dip probe (342 e), multiplesources (344) connected to the probe(s) (342 e), and a detection system(346) connected to the probe(s) (342 e) that may measure the output(transmission) from the source(s) (344) after passing through thesample, where the difference between the input and output is theabsorption amount, i.e., the “fingerprint” of the sample. In variousembodiments, chamber (340) may be a quartz flow-through cell/continuousflow chamber. In exemplary embodiments, sources (344) may includemultiple sources independently connected to reflection and/ortransmission dip probes (342 e) via fiber optic cables (348 a). Forexample, LED source and/or UV source may be connected to a reflectionprobe (342 e), while a 1000-5000 nm NIR source may be connected to atransmission dip probe (342 e). In a particular embodiment, transmissiondip probe (342 e) may be the TP300-Series Transmission Probes offered byOcean Optics, Inc. See FIG. 11A. In an exemplary embodiment, reflectionprobe (342 e) may be the premium-grade reflection probes manufactured byOcean Optics, Inc. See FIG. 10A. In various embodiments, the detectionsystem (346) may utilize a CCD or a set of photodiodes with spectralfilters for measuring the intensity of resultant wavelengths compared tothe source (344). In example embodiments, the use of multiple sources(344) may require additional fiber optic cables (348 b, 348 c, 348 d)connected to probe (342 e) with multiple “eyes” for each cable (348 b,348 c, 348 d), i.e., a different set of photo diodes in detection system(346) for detection of fingerprint data from the sample for each type ofspectroscopy system used. Using additional fiber optic cables (348 b,348 c, 348 d) may allow for the measurement of different types offingerprint data by choosing to apply or not apply a spectral filter foran excitation source (344) wavelength to cable (348 b, 348 c, 348 d).

Although particular embodiments described herein refer to analysis ofoil, fluid analysis system (100) as described herein, including coolingsystem (302), sampling system (304), and/or analytical system (400)described herein may be used to analyze properties of other types offluids, including water (e.g., see FIGS. 1 and 2). In an exemplaryembodiment, fluid analysis system (100) described herein may be a wateranalysis system (100). In embodiments of this water analysis system(100), water may be routed from a water source (200), e.g., a reservoir,into cooling system (302) and/or directly into sampling system (304) toobtain real-time data regarding the fluid. For example, water may beanalyzed in embodiments of the present disclosure to determine thepresence of microorganisms, nitrate, and arsenic.

In various embodiments, cooling system (302), sampling system (304),and/or analytical system (400) of water analysis system (100) mayinclude substantially the same features as oil analysis systems (100)described herein (e.g., see FIGS. 1 and 2). However, in someembodiments, cooling system (302) of water analysis system (100) may notinclude a filter (320). As in oil analysis system (100), cooling system(302) may not be utilized in water analysis system (100) if water is ata sufficiently low temperature for analyzing via sampling system (304).In various embodiments, sampling system (304) of water analysis system(100) may or may not include a viscometer (328) (e.g., see FIG. 7).

Although fluid analysis system (100), including oil analysis system(100) and water analysis system (100), are shown in FIGS. 1 to 13 anddescribed herein as having specificconfigurations/features/applications, these systems are not limited tothese particular configurations/features/applications and otherconfigurations/features/applications may be utilized as suitable toperform analysis of various types of fluids.

Referring to FIG. 14, a schematic of an alternative embodiment of fluidanalysis system (1000) with a nano chip plug (1032) is shown. Fluidanalysis system (1000) may include an enclosure (1002) having a femalepipe thread inlet (1016) and outlet (1018). In an exemplary embodiment,enclosure (1002) may be an 18 in×18 in×6 in metal enclosure, and inlet(1016) and outlet (1018) may be ¼ inch inlets and outlets. In variousembodiments, the inlet of enclosure (1002) may include a shut-off valve(1020) built into the design for safety (in case a line is leaking inthe circuit) and/or for maintenance that may need to be performed on theenclosure (1002) without having to shut the system (1000) down.Additionally, enclosure (1002) may include a reset switch (1014) on oneside for manual reset of the engine/equipment after an oil change hasbeen performed to establish a new baseline for oil analysis.

Enclosure (1002) may also include a controller (1012) with the abilityto control up to 36 fluid analysis sensors. Fluid analysis sensors maybe mounted within enclosure (1002). For example, enclosure (1002) mayinclude multiple types of oil analysis sensors, including but notlimited to sensors with the following properties: oil propertymonitoring capabilities, and/or identification of specific wear metals(1022), moisture levels (1024), particulate counts (1026), viscosity(1028), TAN, TBN, Nitration, Sulfation, Foreign Oils, Solvents, Glycol,Soot, Dissolved Gases, and/or Oil Additive Depletion (Zn, Mo, Ph, Ca,Mg, Ba, Na). See, e.g., FIG. 14. Sensors may be programmed tocommunicate data every two seconds to few minutes to the controller(1012) with a lifespan of five years or longer. In some embodiments,sensors may be provided that may be easily changeable if replacement isrequired. To replace a sensor, shut off the built in shut off valve(1020), open the front cover panel, unscrew the sensor from thecontroller (1012), and unscrew the sensor from the female pipe thread.Once unhooked, replace, and reattach new sensor in the same manner.Controller (1012) may be configured to automatically recognize the newsensor and start collecting data.

In some embodiments, enclosure (1002) may include an electric pump(2004) (e.g., see FIG. 16) that may draw oil out of the attachedequipment/engine, and push the oil through the enclosure (1002) and backto the equipment/engine. Pump may be a 120 v, 240 v, or 480 v electricalpump. Enclosure (1002) may further include a built in pressure reducingvalve on the inlet pressure line. In an exemplary embodiment, thepressure reducing valve may reduce oil pressure from 5000 psi down to 50psi before it goes through the enclosure (1002) and back to theequipment/engine.

In various embodiments, enclosure (1002) may include a 1-micron oilfilter (1030). Oil may flow through the system (1000) in a particularsequence to validate and ensure extended life of the equipment's oil. Inan embodiment, the system (1000) may be configured in the followingorder: Wear metal sensor (1022), Water Sensor (1024), Particle CountSensor (1026), Viscosity Sensor (1028), Oil Parameters Sensor, 1-MicronOil Filter, Particle Count Sensor, Oil Parameter Sensor (e.g., see FIG.16). This sequence may be important in determining the oil purity of theequipment since the 1-micron filter may change the particle count andmoisture content in the oil. System (1000) may extrapolate the wearmetals, water, particle count, viscosity, and parameters before the oilcrosses the 1-Micron filter. System's (1000) ability to calculate thedifference between the readings before and after the 1-Micron filter (asdescribed below with reference to FIG. 16) may allow for accurate oilquality measurement and oil life predictive calculations. Since thesereadings may be on both sides of the 1-Micron filter, a true reading ofthe oil and equipment condition may be realized in the reading (e.g.,see FIG. 16 and related description). Taking readings in this order, onboth sides of the 1-micron filter, may thus further improvepredictability of the lifecycle of the oil and equipment condition.

In exemplary embodiments, system (1000) may further include a nodeenclosure (1004) connected to enclosure (1002). See FIG. 14. Nodeenclosure (1004) may be a 12 in×12 in×6 in weatherproof enclosure withan antenna (1008) for satellite, cell phone, or Wi-Fi connectivity. Nodeenclosure (1004) may track up to six different data inputs into oneaccount. Each data point may relate to a separate enclosure (1002) thatmay be hard wired back to the node enclosure (1004). In addition to thesix hard wired enclosures, system (1000) may be piggy backed togetherwith other systems (1000) for up to 36 different systems (1000) androute back into one connection at the node enclosure (1004). Thisparticular configuration may allow for system (1000) to only have onecommunication node for multiple enclosures (1002)/systems (1000),provide great cost benefits to the consumer, and allow for easier andcleaner installation of the system (1000). Node enclosure (1004) mayfurther include a connection for satellite/Wi-Fi/cell tower antenna(1008) and a power port and/or Ethernet/HDMI port (1010).

Node enclosure (1004) may be outfitted with a rugged node (1006) forcustom programming and algorithms to compute and process sensor inputsand to relay crucial notification abilities via text or email. Theprogramming and algorithms may include oil analysis readings for thefollowing: specific wear metals, moisture levels, particulate counts,viscosity, TAN, TBN, Nitration, Sulfation, Foreign Oils, Solvents,Glycol, Soot, Dissolved Gases, and/or Oil Additive Depletion (Zn, Mo,Ph, Ca, Mg, Ba, Na). The custom programming may also send instantnotifications to the user the moment critical levels are reached asestablished by user-determined preferences or as determined by the NIST(National Institute of Standards and Technology) oil analysis standardsif there are no user-determined preferences are not programmed into thenode (1006). The programming and algorithms may have a predictiveability built into the design of the node (1006) that may notify usersof upcoming preventive maintenance.

In various embodiments, networking capabilities of the system (1000) maybe virtually limitless due to the ability of system (1000) to piggybackenclosures (1002) together. Networking features include: (i) daisychaining up to 36 enclosures (1002) going to one node enclosure (1004);or (ii) wiring up to 36 enclosures (1002) into the node enclosure (1004)directly. Once these multiple enclosures (1002) are transmitting datainto the node enclosures (1004), system (1000) may combine an unlimitednumber of data points into on account that may be accessible by the useron a 24×7 basis via any internet connected device. This may afford theuser full control over the monitoring and maintenance of itsequipment/engine.

In an exemplary embodiment of the present disclosure, oil may bere-routed from the equipment through the systems described herein, andback to the equipment. Once oil is flowing through the system, wearmetals, moisture levels, particulate counts, viscosity, TAN, TBN,Nitration, Sulfation, Foreign Oils, Solvents, Glycol, Soot, DissolvedGases, and/or Oil Additive Depletion (Zn, Mo, Ph, Ca, Mg, Ba, Na),and/or oil temperature reporting may be tested and logged up to every 2seconds. In some embodiments, an additional sensor may be added foremissions monitoring. Each different measurement may be taken via aspecific sensor for each analysis data point. The data may be collectedinto controller (1012) built into the enclosure (1002) described herein.Controller (1012) may transmit the data to the node (1006). In exemplaryembodiments, node (1006) may be a small Linux based computer. Node(1006) may be programmed with custom algorithms to compute and processthe sensor inputs from the controller (1012), and to relay crucialnotifications. Node (1006) may then transmit the data through the bestavailable method: Ethernet cable, Wi-Fi, cell phone signal, or satellitesignal.

Once this data is transmitted, it may be stored in the cloud and thedata may be readily available for the user to access from theircomputer, tablet, or phone. If internet signal drops, node (1006) may befitted with a 60 gigabyte hard drive that may store the informationuntil the internet signal is restored. Once internet is restored, node(1006) may automatically dump all of the data to the cloud basedstorage. If there is critical information gathered from the system, theuser may be notified via text or email. User may log into their accountwith custom designed dashboards so they can see all equipment and datapoints being monitored. Custom dashboards and alerts may be determinedby the user to meet its individual needs. Alerts may be sent to the uservia email or text message automatically from the system algorithms thatmay be programmed for specific data points. The online dashboard may beweb-based and may be accessed from any device that has an internetconnection. The dashboard may automatically collapse and stack the datato for e.g. a tablet and/or cell phone view if the user is not loggingin from a computer/web browser.

Once this system (1000) is installed and parameters have been programmedinto the node (1006), the user may be completely independent from thesupplier in the management and maintenance of its equipment. For acustomer to be completely independent from any oil lab, oil tech,mailing company, and/or technician taking oil samples gives the customerassurance of lack of human errors or time delays of this critical dataduring the systems process. Further, if the user's needs evolve,additional data points may be programmed into the node (1006) ifrequired. If a customer uses a unique type of oil or wants customnotifications when the system (1000) reads any key components from thebuilt in sensors, system (1000) may be custom programmed for thatcustomer's needs. This type of custom programming may be important forlarger customers having engine manufacturers that require certain keyelements monitored.

In some embodiments, the system (1000) described herein may be used toperform real time oil analysis sampling from multiple pieces ofequipment. Sampling from multiple pieces of equipment may beaccomplished through customized multi-flow control valves that may allowoil to be brought in from multiple pieces of equipment using the sametype of oil. In embodiments, the pieces of equipment may be located inthe same vicinity as each other and system (1000). In other embodiments,the pieces of equipment may be located further away/remotely from eachother and system (1000).

Multi-flow control valves may be controlled via custom designeddashboards as described herein. Multi-flow control valves may beconfigured as manifold-control valve connections. Flow control valvesmay be inlet multi-flow control valves and/or outlet multi-flow controlvalves. System (1000) may include an inlet multi-flow control valveprogrammed to allow oil to flow into an enclosure (1002) from only oneengine at a time via an inlet valve described herein (e.g., see FIGS. 4and 6). System (1000) may further include an outlet multi-flow controlvalve programmed to allow for the oil to be returned to the same enginefrom which it was pulled via an outlet valve described herein and areturn line going back to the same equipment (e.g., see FIGS. 4 and 6).In an exemplary embodiment, once an analysis is made over a period of 2to 5 minutes, the inlet valve may switch off, at which time the systemmay be programmed to notify another valve to open for a next piece ofequipment that may have been programmed in a sampling sequence. In someembodiments, a delay of 60 to 180 seconds may occur between the openingof a new valve and for the system (1000) to start taking readings toclean out the lines feeding the system (1000). In other embodiments,this sequence of changing between different pieces of equipment may beprogrammed from every few minutes, to once an hour, per piece ofequipment depending on a customer's needs.

In exemplary embodiments, once system (1000) is taking readings fromeach different motor/equipment in the area, it may be configured to thenrun comparative algorithms in a separate custom designed dashboarddescribed herein, and thereby perform comparative analysis of oils fromdifferent equipment to determine which engines may be running mostefficiently and which engines may be in need of extra attention,modifications, and/or service. Detailed reporting may allow forcustomers to pinpoint any problems with efficiency in different piecesof equipment and solve any problems that they may not have knownexisted. Further, this reporting may also allow the customers todetermine themselves which engines are running most efficiently andwhich engines may need to be replaced.

In particular embodiments, system (1000) may be retrofitted with a nanochip plug (1032) technology (e.g., see FIGS. 14 and 16) to perform realtime oil analysis of a fluid after the fluid has passed through severalsensors (1022, 1024, 1026, 1028) as described herein. See FIG. 14. FIG.15 is an illustration of interior components of the nano chip plug(1032). Nano chip plug (1032) may utilize a spectralscanner/spectrometer (1034) to instantaneously and continuously scan andinform a user of the molecular makeup and condition of any industrialoil. As described herein, different types of fluids/materials have theirown “fingerprint” and nano chip plug (1032) may read and analyze thedifferences between these materials and obtain this “fingerprint”information of the fluids via spectroscopy. In exemplary embodiments,nano chip plug (1032) may have a size less than approximately 1 inch×1inch. In other embodiments, the nano chip plug (1032) may have othersizes and configurations to perform real time oil analysis. Embodimentsof the present disclosure provide for several different options that maycover a variety of industries and applications, including but notlimited to oil and gas, maritime, aerospace, government, agriculture,water, waste water, lube oils, hydraulic oils, gear oils, coolants, etc.Embodiments of the systems described herein may be able to work with anytype of industrial fluid.

In exemplary embodiments, nano chip oil plug (1032) may be used for realtime oil analysis by integrating a nano chip and spectrometer (1034)into an oil plug. See, e.g., FIG. 15. The oil plug may be any plug thatmay access the fluid being analyzed. In an exemplary embodiment, anexisting oil plug in an engine/equipment may be removed, and a nano chipoil plug (1032) may be installed onto the engine/equipment in place ofthe existing oil plug.

Embodiments of the present disclosure may further utilize a database asdescribed herein in conjunction with the systems described herein. In anexemplary embodiment, a “fingerprint” of a sample of a particular typeof oil [for e.g., Shell Rotella 15W-40] in a particular engine [fore.g., Caterpillar Cat® 3516B diesel generator] may be analyzed andcollected via the system (1000) with the nano chip plug (1032). This“fingerprint” information may then be transmitted to a node (1006) asdescribed herein, which may then transmit this information to a databaseas described herein via any of the systems described herein. Database(e.g., system 1000 of FIG. 14) may then compare this fingerprintinformation to existing information stored in the database for thatparticular type of oil and its conditions, including but not limited tothe presence of any wear metals in the oil being analyzed. In aparticular embodiment, node (1006) (e.g., see FIG. 14) may connect tothe cloud and run a comparative analysis algorithm between thisfingerprint information and existing information on the database for thesame type of oil to determine a precise makeup of this particular oilsample. Doing so may allow for the detection of the presence of severalconditions in this oil sample, including but not limited to the presenceof wear metals, as well as the diagnosis of any particular problems withthe engine. In exemplary embodiments, this process involving comparisonand analysis of the current and existing real-time data may only takeabout 2 to 30 seconds. System (1000)/database may then relay theconclusions from this comparative analysis to customers requesting theinformation. In embodiments, this information may be sent to customersvia email, text, website software, and/or any other available methods ofcommunicating such information.

By comparing new scans to the existing database of sample scans, system(1000) may instantaneously provide the condition of the fluid sample. Insome embodiments, system (1000) may be continuously grown by scanningand adding additional sample types as they become available, thusincreasing the accuracy of the overall system's detecting abilities.Database may be accessed via the internet, cell phone signal, satelliteconnection, and/or any other available connection to external sources.In various embodiments, database may be grown via “training” in a neuralnetwork as described herein.

FIG. 16 is a schematic of an alternative embodiment of fluid analysissystem (2000) with the nano chip plug (1032) described herein. As shown,fluid analysis system (2000) with the nano chip plug (1032) describedherein may be constructed to install at an engine oil pressure galleyand bypass the engine back to the oil filler neck. In the bypass loop,oil may be flowed/routed from equipment fluid access point, Y, through aprogrammable flow control valve (2002). Flow control valve (2002) may beprogrammed to open and close to allow oil to flow through system (2000).Oil may be stationary in the system (2000) once the valve (2002) isclosed during a scan. This option may be added to allow for a moredetailed oil sample to scan the oil while it is stable and not flowingat, for e.g., 50 psi. Once the scan is complete, the valve (2002) mayopen and allow oil to flow through the system (2000) until the nextsampling time. In exemplary embodiments, this next sampling time mayoccur as soon as every 30 seconds. However, this system (2000) may beconfigured to take samples in any other time as needed.

Oil may be routed through a pump (2004) to provide pressure when thereis no oil/fluid pressure available. See FIG. 16. In various embodiments,oil may then be routed through a pressure reducing valve (2006), oilcooler (2008), and push button oil sample valve (2010 a) installed forsampling of the oil before it reaches nano chip plug (1032 a). Oilcooler (2008) may be used inline if the oil being routed through thesystem (2000) is too hot. From nano chip plug (1032 a), oil may berouted to a 1 micron bypass oil filter (2014) to allow for more detailedanalysis and further prolong engine oil life via extra filtration of theoil sample. In exemplary embodiments, another nano chip plug (1032 b)may be added after the 1 micron bypass oil filter (2014). The 1 micronoil filter (2014) may be inline of a bypass loop and may take a scanbefore and after fluid/oil passes through the filter (2014) in order tocompare and determine how well the filtration is performing and howexactly the filter (2014) is impacting the fluid/oil sample. Thisparticular configuration is unique because once this additional nanochip plug (1032 b) is added, the before and after readings of thesamples may be compared and analyzed, which data may then be used toprolong the life of the oil and provide a measureable impact that thefilter (2014) may be having on the oil. In contrast, it is virtuallyimpossible to show the measureable impact of an oil filter (2014) inreal time in existing systems. On the way back to the engine's oilfiller neck into equipment's fluid return point, Z, oil may be passedthrough another push button oil sample valve (2010 b).

Fluid analysis system (2000) may be used to gather samples and/or addrelevant data from the samples to a database. Fluid analysis system(2000) may be connected to and transfer data from the samples to a node(1004) (e.g., see FIG. 14) as described herein, which may then transmitthe data to a database as described herein. Database may be located inthe cloud or in any known external device. In some embodiments, the nodeitself may house the database.

FIG. 17 is a flowchart of a fluid analysis system (100) as describedherein using cooling system (302) and sampling system (304), includingrelated software in controller (332) (e.g., see FIG. 7) of samplingsystem (304) and/or cooling system (302), as described herein (e.g., seeFIGS. 1 to 6). Fluid analysis system (100), cooling system (302), andsampling system (304) described in FIG. 17 may be implemented using theapparatuses, systems and methods described herein, including variousembodiments thereof. As shown in FIG. 17, fluid analysis system (100)may include the following steps.

In an exemplary embodiment, software of controller (332) (e.g., see FIG.7) of sampling system (304) may first run a self-diagnostics check todetermine whether excitation source (344) and/or valves (312 and 314 ato 314 d) are operational and for any error conditions from coolingsystem (302) and sampling system (304). If the initial self-diagnosticscheck shows error conditions, controller (332) may report theseerrors/failures and any related failure codes to the analytical system(400), and ensure the excitation source (344) is powered off and thatall valves (312 and 314 a to 314 d) are closed (if possible). If theinitial self-diagnostics check does not show any error conditions, thensub-sampling system (330) may be powered on. Again, if error conditionsarise, controller (332) may report these errors/failures and any relatedfailure codes to analytical system (400), and ensure the excitationsource (344) is powered off and that all valves (312 and 314 a to 314 d)are closed (if possible). If no error conditions are produced uponpowering on of the sub-sampling system (330), controller (332) may senda signal to cooling system (302) to close the temperature loop describedherein relating to action of pressure reducer valve (308, 308 a, and 308b) (e.g., see FIGS. 3 to 7), cooler (324), temperature sensor (310), and2-way solenoid valve (312), open fluid return and fluid out valves (314a to 314 d), and enable cooler (324) and fan (370) to cool fluid.

If the temperature >40° C., oil may be re-routed back to cooler (324) asdescribed herein for further cooling. If the temperature <=40° C.,bypass valve (312) may be opened to allow fluid through to samplingsystem (304). Once in sampling system (304), controller (332) may use alength parameter to calculate overall cycle time and begin a timer.Particularly, if there are multiple fluid sources (200), and one source(200) is significantly further away from another source (200), samplingsystem (304) may have to cycle the fluid for a longer time to ensure thesub-sampling system (330) is not contaminated. If the timer has notexpired, controller (332) may utilize sensor/transducer (308B) locatedat output/return line of sampling system (304) (e.g., see FIG. 7) toperform a pressure comparison between the input and output pressures todetermine if a significant enough drop exists to identify the presenceof a leak. If so, controller (332) may report this failure and anyrelated failure codes to analytical system (400), and ensure theexcitation source (344) is powered off and that all valves (312 and 314a to 314 d) are closed (if possible).

If the difference between the input and output pressures is notsignificant, controller (322), and the timer has expired, controller(332) may close all valves (312 and 314 a to 314 d) to stop movement ofthe fluid and begin sampling of fluid using sampling system (304) asdescribed herein. In various embodiments, sampling system (304) may thenbegin fluid sample acquisition as described herein, use viscometer (328)to obtain viscosity measurement of the fluid, and/or use temperaturesensors (310) to measure temperature of the fluid as described herein(e.g., see FIG. 7). In exemplary embodiments, sampling system (304) maythen take 13 to 20 samples of each sample type and send these sampledata sets to controller (332), which controller (332) may then submitthe sample data sets to analytical system (400) as described herein.

In various embodiments, controller (332) may send a signal to coolingsystem (302) to end its cycle. For example, fan (370) may terminate whencooler (324) reaches an ambient air temperature as described herein.Once the fluid is adequately sampled by sampling system (304), fluid maybe routed back from sampling system (304) to cooling system (302). Tofacilitate this return, controller (332) may open return air valve (322)(e.g., see FIGS. 3 to 6) in cooling system (302) as needed to allow airto purge the line and speed up the return of fluid if there is nopressure to push/gravity drain the fluid back into cooling system (302)from sampling system (304). Controller (332) may then determine whetherthe timer described herein has expired. If so, controller (332) mayclose air valve (322) and power off sub-sampling system (330) and/orsampling system (304).

FIG. 18 is a flowchart of analytical system (400) as described herein,including command and control system (406) and database (402) describedherein. Analytical system (400), command and control system (406),and/or database (402) described in FIG. 18 may be implemented using theapparatuses, systems and methods described herein, including variousembodiments thereof.

As described herein, command and control system (406) may be a hostedsoftware system that may receive the submitted sample data sets of thefluid and process it through a set of neural network models forpredictive analysis. The neural network models may be configured totarget any type of fluid to be analyzed. The resulting output of thesample analysis may be dependent on the fluid submitted, the networksprocessed and the statistical percentage accuracy for the given networkmodel.

The output from a spectral sample is known as a spectral wave. This maybe visualized as a set of coordinate points, x (usually for wavelengthor in Raman the shift), and Y (usually an intensity value seen at thatwavelength point). These graphs of data (points) may then be uploaded tothe analytical system (400) where it may be stored, assessed andpresented to a neural network model for concrete identification andsystem prediction. In order for spectral samples to have any context,known samples must be obtained prior to receiving fluid samples so thata baseline may be established for a specific neural network. A neuralnetwork may be composed of three layers: an input layer, hidden layer,and output layer, with each layer including one or more nodes whereinformation flows between the nodes.

If the type of sample cannot be identified, neural networks may require“training”, i.e. inputting of known parameters associated with types ofsamples/sub-sampling systems (330) to assist in identification of thesamples and strengthen the resulting neural network model. A neuralnetwork model represents the knowledge of the neural network. Asdescribed herein, a neural network model may be created from known datasets. Therefore, when a sample is submitted, the parameters for whichthe sample was collected may be required to identify the particularneural network to use for identification. For example, a neural networkfor the fluid analysis systems (100, 1000, 2000) (e.g., see FIGS. 1, 2,14, and 16, respectively) described herein may be defined by thefollowing set of parameters, including but not limited to the type ofsub-sampling system (330) used, wavelength of electromagnetic radiation(or if it's monochromatic), viscosity, temperature, and pressure. Theseparameters may define the network and its' subsequent model. Known datasets, i.e., a spectral sample of fluid (e.g., clean oil) with x ppm of yelements combined with the above determined parameters may allow for“training” of a network and creation of a model. The more known (good)data that can be trained into a neural network, the higher the accuracyand success rate of identifying unknown samples. In exemplaryembodiments, building neural network models may require the use ofimmense computational resources. To that end, building of these modelsmay occur in the analytical system (400) in the cloud with modelspotentially pushed to the sampling system (304) if onboard analysis isrequired.

In exemplary embodiments, a user may access and/or modify the analyticalsystem (400) via for e.g. a web application (HTTP/HTTPS) in a computingdevice through any type of encrypted connection described herein. Inexemplary embodiments, user may log in to the database (402), and basedon his/her role and security permissions, be shown a dashboard ofavailable sampling systems (304), messages (either predictive analysismessages based on samples), error messages, and/or training requestmessages. In various embodiments, the user may select a specificsub-sampling system (330), interact with the sampling system (304) andask the sampling system (304) to perform analysis and obtain a fluidsample, configure the system (304) (i.e., setup the automated samplingtimeframe), analyze the real time parameters coming from the system(304) (for e.g. temperature, last time sample taken, pressure, fluidtemperature, etc.). In some embodiments, the user may also add newsub-sampling systems (330) to a client and/or de-authorize or shutdownexisting sampling systems (330). User may also, if available, issue asoftware update to sampling system (304) and/or cooling system (302),view analytical neural networks and related network statistics, and alsoview the number of known good samples, percentage of successfulidentification, accuracy threshold, and/or force a retrain or modeldiagnostic.

Referring back to FIG. 18, analytical system (400) may include thefollowing steps. Command and control system (406) of analytical system(400) may first receive submitted sample data sets of the fluid beinganalyzed from controller (332). See FIG. 17. Upon receipt of thesesample data sets, command and control system (406) may first retrieveclient/system information and sampling system (304) configurationassociated with the sample. If the client/system information andsampling system (304) configuration cannot be retrieved from thesubmitted sample data sets, system (400) may show a “log error” andcommand and control system (406) may interact with database (402) topresent this log error to a user via web application as describedherein, so that the user may make appropriate modifications asnecessary. If the data is valid, command and control system (406) maysubmit the data sets to a model engine as a sample based on theclient/system/sampling system (304) configuration. In exemplaryembodiments, command and control system (406) may also store this sampledata set in database (402) described herein.

Command and control system (406) may then verify that a submission queueis available for a specific model/system configuration. For example, ifthe sample is a type of oil with a viscosity of X, and Ramansub-sampling system (330, 350) with a wavelength of 785 nm is used toperform analysis of the oil, command and control system (406) may searchthe database (402) for and utilize a model matching those exactparameters to determine the identity of the sample of oil.

If a submission queue is not available, system (400) may show a “logerror” and command and control system (406) may interact with database(402) to present this log error to a user via web application asdescribed herein, so that user may make appropriate modifications asnecessary. If a submission queue is available, command and controlsystem (406) may then submit each data set to the corresponding neuralnetwork model as described herein. Neural network model may then processresults based on each data set as described herein, which results maythen be sent to database (402) by command and control system (406). Ifany issues arise with submitting each data set to the neural networkmodel, system (400) may show a “log error” to user as described herein.

Once fluid analysis results are processed by a neural network model,command and control system (406) may notify the user if these resultsmeet certain defined analysis thresholds for the samples/type ofsampling system (330). If so, command and control system (406) may endsubmission of the data sets to the neural network model.

Command and control system (406) may then determine whether the systemrequires “training” as described herein. If not, command and controlsystem (406) may end submission of the data sets to the neural networkmodel. However, if the system does require training, command and controlsystem (406) may notify the user that appropriate training is required.In exemplary embodiments, user may then (via a web application) supplycertain training inputs to command and control system (406) for eachsample for which training is requested. Command and control system (406)may use these training inputs to update/rebuild the neural networkmodels or create new neural network models with the new data obtainedfrom the fluid sample data sets. Command and control system (406) maythen store the updated/new models in database (402), and/or deploy theupdated/new models back to sampling system (304). In variousembodiments, user may access existing and updated neural network models,and related data, in database (402) via for e.g. a web application asdescribed herein.

Embodiments provide methods for performing fluid analysis. Methods mayinclude using the fluid analysis system (100) described herein,including cooling system (302), sampling system (304), and analyticalsystem (400) including command and control system (406) and database(402) described herein. In an exemplary embodiment, the method includesrouting fluid through the removable and replaceable sampling system(304) described herein, collecting real-time data from the fluid via thesampling system (304), and processing and transmitting the real-timedata to the analytical system (400) described herein connected to thesampling system (304). The method may include routing the fluid througha removable and replaceable cooling system (302) for cooling the fluidprior to being routed through the sampling system (304). In exemplaryembodiments, the method may include receiving the real-time data via thecommand and control system (406) and processing it through a set ofexisting neural network models for the fluid in the database (402) forpredictive analysis. The method may include updating the existing neuralnetwork models or building new neural network models if the real-timedata does not correspond to any of the set of existing neural networkmodels. The method may further include deploying the updated or newneural network models back to the sampling system (304).

Embodiments of the present disclosure may be utilized in a multitude ofreal-world applications and industries requiring fluid analysis,including but not limited to in oil and gas drilling rigs onshore andoffshore, oil and gas pipelines, oil processing and chemical plants,offshore vessels, river work boats, freight trucks, any large commercialengines, and systems related to analysis of municipal water quality,remote water quality (well, rain water, aquifer, bottled), engine oil,hydraulic oil, transmission oil, coolant, fuel (in system and atstation), milk bottling plants, beer kegging/bottling plants, industrialwaste water, shipped crude oil, and/or urine.

Embodiments of the present disclosure may provide for more accuratereal-time application data, increased resale value of equipment byproviding history documentation in the cloud, improved oil analysistrending through better accuracy and consistency of sampling, low coststrategies to equip all critical systems, reduced current manpowerdemands, reduced risk-based costs and offering of failure preventionthrough root-cause monitoring, minimized operator exposure to safety andhealth hazards while sampling, reduced risk of spillages duringsampling, and thus reduced H&S issues, particularly for users in the“Food-safe” oils industries, reduction/elimination of practice ofdisposal of samples and use of reagents at the laboratory, maximizedinformation for optimum maintenance planning extending drain intervals,allowing for oil to stay in a clean state for longer periods per theNIST standards, extended oil drain intervals, improved reduction ofsolid, liquid, and/or gaseous contaminants from oils, increased engineand equipment life, and reduced operating costs.

While the embodiments are described with reference to variousimplementations and exploitations, it will be understood that theseembodiments are illustrative and that the scope of the disclosures isnot limited to them. Many variations, modifications, additions, andimprovements are possible. Further still, any steps described herein maybe carried out in any desired order, and any desired steps may be addedor deleted.

What is claimed is:
 1. A system for analyzing an oil, comprising: asample chamber coupled to a source engine and configured to receive aportion of an oil circulating through the source engine; a laser deviceoptically coupled to the sample chamber and configured to transmit afirst electromagnetic radiation to the portion of the oil; acharge-coupled device (CCD) sensor optically coupled to the samplechamber and configured to detect a second electromagnetic radiationemitted from the portion of the oil in response to the firstelectromagnetic radiation, the CCD sensor generating a spectral data setusing at least the second electromagnetic radiation; and a computingdevice operationally connected to the laser device and the CCD sensor,the computing device receives the spectral data set for analysis.
 2. Thesystem of claim 1, further comprising at least two second laser devicesoptically coupled to the sample chamber, wherein a first one of the atleast two laser devices is configured to transmit a thirdelectromagnetic radiation to the portion of the oil, and wherein asecond one of the at least two second laser devices is configured totransmit a fourth electromagnetic radiation.
 3. The system of claim 2,further comprising at least two second CCD sensors optically coupled tothe sample chamber, wherein a first one of the at least two second CCDsensors is configured to detect a fifth electromagnetic radiationemitted from the portion of the oil in response to the thirdelectromagnetic radiation, and wherein a second one of the at least twosecond CCD sensors is configured to detect a sixth electromagneticradiation emitted from the portion of the oil in response to the fourthelectromagnetic radiation.
 4. A system for analyzing an oil, comprising:a sample chamber that houses an oil sample from a source engine; anoptical detection apparatus operationally connected to the samplechamber, the optical detection apparatus includes: an excitation sourceapparatus configured to transmit a first electromagnetic radiation tothe oil sample; and an emission detection apparatus configured to detecta second electromagnetic radiation emitted from the oil sample inresponse to the first electromagnetic radiation, the emission detectionapparatus generates, using at least the second electromagneticradiation, optical spectroscopy data associated with an optical propertyof the oil sample; and an analytical apparatus operationally connectedto the optical detection apparatus, the analytical apparatus configuredto receive the optical spectroscopy data from the optical detectionapparatus and further configured to determine a condition of the oilsample using at least the optical spectroscopy data, wherein todetermine the condition of the oil sample, the analytical apparatus isfurther configured at least to: remove a portion of the opticalspectroscopy data, resulting in second optical spectroscopy data;determine baseline data from the second optical spectroscopy data;subtract the baseline data from the portion of the second opticalspectroscopy data, resulting in third optical spectroscopy data; andapply a neural network model to the third optical spectroscopy data. 5.The system of claim 4, wherein the condition of the oil sample analyzedcomprises determining one or more of: presence of a wear metal in theoil sample, presence of an amount of an additive in the oil sample,viscosity of the oil sample, presence of water in the oil sample, totalacid number (TAN) of the oil sample, presence of coolant in the oilsample, presence of fuel in the oil sample, total base number (TBN) ofthe oil sample, dilution of the oil sample, or a particle count ofparticulate matter within the oil sample.
 6. The system of claim 4,wherein the analytical apparatus is further configured to determine atleast one parameter representative of the condition of the oil sample.7. The system of claim 4 wherein the analytical apparatus comprises oneof a local computer system or a remotely located computer system.
 8. Thesystem of claim 4, wherein the optical detection apparatus furtherincludes a second excitation source apparatus configured to transmit athird electromagnetic radiation to the oil sample, and at least oneemission detection apparatus.
 9. The system of claim 4, wherein thefirst electromagnetic radiation includes wavelengths in a range fromabout 250 nm to about 1500 nm.
 10. The system of claim 6, wherein theexcitation source apparatus is configured to transmit the firstelectromagnetic radiation having a wavelength ranging from about 600 nmto about 900 nm, and wherein the second excitation source apparatus isconfigured to transmit the third electromagnetic radiation having awavelength ranging from about 600 nm to about 900 nm.
 11. The system ofclaim 6, wherein the excitation source apparatus is configured totransmit the first electromagnetic radiation having a wavelength rangingfrom about 680 nm to about 800 nm, and wherein the second excitationsource apparatus is configured to transmit the third electromagneticradiation having a wavelength ranging from about 680 nm to about 800 nm.12. The system of claim 6, wherein the excitation source apparatus isconfigured to transmit the first electromagnetic radiation having awavelength ranging from about 250 nm to about 800 nm, and wherein thesecond excitation source apparatus is configured to transmit the thirdelectromagnetic radiation having a wavelength ranging from about 800 nmto about 1500 nm.
 13. The system of claim 6, wherein a wavelength of thefirst electromagnetic radiation is different from a wavelength of thethird electromagnetic radiation.
 14. The system of claim 4, wherein theoptical detection apparatus further includes at least one of aviscometer device; a temperature sensing device; a fluorescence samplingapparatus; an absorbance sampling apparatus; a Fourier Transforminfrared (IR) absorbance sampling apparatus; a Raman scatteringapparatus; an absorbance-fluorescence-scatter sampling or apparatus. 15.The system of claim 4, wherein the source engine includes a first engineand a second engine.
 16. The system of claim 15, wherein the oil sampleincludes a first amount of oil from the first engine and a second amountof oil from the second engine.
 17. The system of claim 4, wherein thesource engine includes one or more of a two-stroke engine, a four-strokeengine, a reciprocating engine, a rotary engine, a compression ignitionengine, a spark ignition engine, a single-cylinder engine, an inlineengine, a V-type engine, an opposed-cylinder engine, a W-type engine, anopposite-piston engine, a radial engine, a naturally aspirated engine, asupercharged engine, a turbocharged engine, a multi-cylinder engine, adiesel engine, a petrol engine, a gas engine, or an electric engine. 18.A fluid analysis system, comprising: an excitation source configured togenerate incident electromagnetic radiation; a detection systemconfigured to detect scattered/emitted electromagnetic radiation; afluid inlet configured to mechanically couple to a fluid source and toreceive a fluid sample from the fluid source; a removable andreplaceable sampling system comprising: a sample chamber fluidicallycoupled to the fluid inlet and configured to receive the fluid samplefrom the fluid source; a probe optically coupled to the sample chamber,to the excitation source, and to the detection system, the probeconfigured: to receive the incident electromagnetic radiation fromexcitation source and to deliver the incident radiation to the fluidsample; and to receive scattered/emitted radiation from the fluid sampleand to deliver the scattered/emitted radiation to the detection system.19. An engine oil analysis system, comprising: an excitation sourceconfigured to generate incident electromagnetic radiation; a detectionsystem configured to detect scattered/emitted electromagnetic radiation;a oil inlet configured to mechanically couple to an engine source and toreceive an oil sample from the engine source; a removable andreplaceable sampling system comprising: a sample chamber fluidicallycoupled to an oil inlet and configured to receive the oil sample fromthe engine source; a probe optically coupled to the sample chamber, tothe excitation source, and to the detection system, the probeconfigured: to receive the incident electromagnetic radiation from theexcitation source and to deliver the incident radiation to the oilsample; and to receive scattered/emitted radiation from the oil sampleand to deliver the scattered/emitted radiation to the detection system.20. The system of claim 19, wherein the probe optically coupled to thesample chamber is a Raman probe.
 21. The system of claim 19, wherein theengine source includes a first engine and a second engine.
 22. Thesystem of claim 19, wherein the excitation source is configured togenerate incident electromagnetic radiation at a wavelength betweenabout 250 nm and about 1500 nm.
 23. The system of claim 22, wherein theincident electromagnetic radiation at a wavelength between about 600 nmand about 800 nm.
 24. The system of claim 19, wherein the samplingsystem further includes at least one non-optical sensor.
 25. The systemof claim 24, wherein the non-optical sensor includes a viscometer and atemperature sensor.